DynSP is inspired by STAGG, a search-based semantic parser [1]} and the dynamic neural module network (DNMN) [2]}.
Like STAGG, DynSP pipelines a sequence of modules as search progresses; but these modules are implemented using neural networks, which enables end-to-end training as in DNMN.
Note that in DynSP the network structure is not predetermined, but are constructed dynamically as the parsing procedure explores the state space.
Figure REF  shows the types of actions and the number of action instances in each type, defined in [3]}.
Consider the example in Figure REF , one action sequence that represents the parser is
